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Cluster formation and evolution in networks of financial market indices

Author

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  • Sandoval , Leonidas Junior

    (Insper, Instituto de Ensino e Pesquisa Rua Quatá)

Abstract

Using data from world stock exchange indices prior to and during periods of global financial crises, clusters and networks of indices are built for asset graphs based on distance thresholds and diverse periods of time, so that it is then possible to analyze how clusters are formed according to correlations among indices and how they evolve in time, particularly during times of financial crises. Further analysis is made on the eigenvectors corresponding to the second highest eigenvalues of the correlation matrices, revealing a structure peculiar to markets that operate in different time zones. We also study the survivability of connections and of clusters through time and the influence of noise in centrality measures applied to the networks of financial indices. The results show how the world’s main stock market indices evolved in the last few decades with respect to their clustering structure, how their connections survive in time, and which indices are more central, according to different criteria. In particular, we witness the early formation and evolution of two main clusters, an American and an European one, the formation of a Pacific Asian cluster, and later on, of an Arab cluster. This analysis complements previous studies of the interdependencies of stock markets worldwide

Suggested Citation

  • Sandoval , Leonidas Junior, 2013. "Cluster formation and evolution in networks of financial market indices," Algorithmic Finance, IOS Press, vol. 2(1), pages 3-43.
    • Handle: RePEc:ris:iosalg:0023
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    Citations

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    Cited by:

    1. Carlos León & Geun-Young Kim & Constanza Martínez & Daeyup Lee, 2017. "Equity markets’ clustering and the global financial crisis," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1905-1922, December.
    2. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 227-243.
    3. Bekiros, Stelios & Nguyen, Duc Khuong & Sandoval Junior, Leonidas & Uddin, Gazi Salah, 2017. "Information diffusion, cluster formation and entropy-based network dynamics in equity and commodity markets," European Journal of Operational Research, Elsevier, vol. 256(3), pages 945-961.
    4. Zeitsch, Peter J., 2019. "A jump model for credit default swaps with hierarchical clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 737-775.
    5. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    6. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    7. Nobi, Ashadun & Lee, Jae Woo, 2016. "State and group dynamics of world stock market by principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 85-94.
    8. Leonidas Sandoval Junior & Asher Mullokandov & Dror Y. Kenett, 2015. "Dependency Relations among International Stock Market Indices," JRFM, MDPI, vol. 8(2), pages 1-39, May.
    9. Leonidas Sandoval Junior, 2014. "Dynamics in two networks based on stocks of the US stock market," Papers 1408.1728, arXiv.org, revised Aug 2014.

    More about this item

    Keywords

    networks; financial markets; cluster; evolution;
    All these keywords.

    JEL classification:

    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • G00 - Financial Economics - - General - - - General

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